魯灰英文怎麼說
魯灰 的英文翻譯
魯灰 英文 lord grey 魯 : Ⅰ名1 (山東的別稱) another name for shandong province2 (姓氏) a surname Ⅱ形容詞1 (遲鈍; 笨) ... 灰 : Ⅰ名詞1 (物質燃燒后剩下的粉末狀的東西) ash 2 (塵土; 某些粉末狀的東西) dust 3 (特指石灰) lime...
魯灰 例句
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Louis surveyed me with his shrewd gray eyes and shook his head portentously.魯 易用他狡猾的 灰 色眼睛打量著我,預示兇兆般地搖著頭。
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In the company there are many mines, such as blue limestone, shandong grey, rust stone, yellow sand stone, white dot limestone, aga red and etc., which have rich deposit, complete mine body as well as convenient communication擁有天青石石 灰 巖、 魯灰 、銹石、黃砂巖、雪花青、將軍紅等多座礦山,儲量豐富,礦體完整,交通便利。
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Secondly, image enhancement technique based on linear filtering is adopted. a new image segmentation method by means of automatic multilevel threshold is given, which realizes partial multilevel threshold segmentation based on image region partition of gray - level position projection, removes the influence of uneven illuminance or uneven gray - level distribution on goal recognition, and resolves the problem of error segmentation caused by threshold step between adjacent regions by threshold transition. the method has well robustness在圖像處理時,採用基於線性濾波的圖像增強方法,並提出了一種新的自動多閾值圖像分割方法,該方法以基於 灰 度位置投影的圖像分區實現局部多閾值分割,克服了不均勻照明或不均勻 灰 度分佈對目標識別的影響,同時,通過閾值過渡很好地解決了相鄰區域閾值「階躍」引起的錯誤分割問題,具有很好的 魯 棒性。
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This method could be used for reference by other fp technology, and also by other biometric, image and pattern recognition and classification, etc. the main conclusion, the shortage and the prospect of the research of this thesis are given finally. structure - based fp recognition method not only makes best use of texture structure information contained in the gray level fp image but also reflect the local information基於結構的指紋識別演算法充分利用了蘊含在指紋 灰 度圖像中的豐富的紋理結構信息,又能反映局部信息(細節點) ,因而彌補了傳統方法在小面積指紋的識別上的不足;基於anfis的匹配演算法和指紋的補償識別演算法,對于指紋圖像中的噪聲和變形有著很好的 魯 棒性,達到了令人滿意的識別準確率。
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Active shape model ( asm ) proves good performance on object localization in gray level images. the model shows its better robustness compared to other localization methods because of the use of the priori knowledge. but the localization performance depends on initial position excessively主動形狀模型( asm )在 灰 度圖像的目標定位中取得了較好的效果,由於利用了先驗知識,因此在目標定位中比其他定位方法具有更好的 魯 棒性,但是定位性能過分依賴于模型的初始位置。
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